From the Ted Talk "Anthony Goldbloom: The jobs we'll lose to machines -- and the ones we won't"

Unscramble the Blue Letters

Machine learning started inmagk its way into industry in the early '90s. It started with relatively ipslmesskat. It started with things like issessnag credit risk from loan applications, sorting the mail by reading handwritten characters from zip codes. Over the past few years, we have made dramatic breakthroughs. Machine learning is now capable of far, far more complex tasks. In 2012, Kaggle challenged its community to build an algorithm that could grade high-school essays. The winning halmsrtgoi were able to match the grades given by human teachers. Last year, we isesud an even more difficult challenge. Can you take images of the eye and diagnose an eye disease lcldae diabetic ypthenotira? Again, the winning algorithms were able to match the diagnoses given by human ophthalmologists.

Open Cloze

Machine learning started ______ its way into industry in the early '90s. It started with relatively ___________. It started with things like _________ credit risk from loan applications, sorting the mail by reading handwritten characters from zip codes. Over the past few years, we have made dramatic breakthroughs. Machine learning is now capable of far, far more complex tasks. In 2012, Kaggle challenged its community to build an algorithm that could grade high-school essays. The winning __________ were able to match the grades given by human teachers. Last year, we ______ an even more difficult challenge. Can you take images of the eye and diagnose an eye disease ______ diabetic ___________? Again, the winning algorithms were able to match the diagnoses given by _____ ophthalmologists.

Solution

assessing

simple

issued

retinopathy

tasks

algorithms

human

making

called

Original Text

Machine learning started making its way into industry in the early '90s. It started with relatively simple tasks. It started with things like assessing credit risk from loan applications, sorting the mail by reading handwritten characters from zip codes. Over the past few years, we have made dramatic breakthroughs. Machine learning is now capable of far, far more complex tasks. In 2012, Kaggle challenged its community to build an algorithm that could grade high-school essays. The winning algorithms were able to match the grades given by human teachers. Last year, we issued an even more difficult challenge. Can you take images of the eye and diagnose an eye disease called diabetic retinopathy? Again, the winning algorithms were able to match the diagnoses given by human ophthalmologists.